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Record W3155705351 · doi:10.3390/jrfm14040176

Impact of Audit Committee Quality on the Financial Performance of Conventional and Islamic Banks

2021· article· en· W3155705351 on OpenAlexvenueno aff
Achraf Haddad, Anis El Ammari, Abdelfattah Bouri

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAudit committeeSolvencyAccountingIslamAuditBusinessMarket liquidityProfitability indexFinancial crisisQuality auditSubprime crisisFinancial systemAudit evidenceQuality (philosophy)Joint auditFinanceEconomicsInternal audit

Abstract

fetched live from OpenAlex

A lot of previous research studied the relationship between audit committee quality and the financial performance of conventional banks before and during the subprime crisis, whereas some other investigations analyzed the same association in the framework of Islamic banks. However, no study has compared these two correlations either before, during, or after the subprime crisis. Several reasons explain the differences, such as the audit committee quality of each bank type, the evaluation method of the financial performance, the research peculiarities, the methodology, the data, and the interpretation. This research aims to compare the impacts of the audit committees’ quality on the financial performance of Islamic and conventional banks between 2010 and 2019. The financial performance measures and audit committees’ determinants of the conventional and Islamic banks concerned 112 banks of each type. The collected data covered four continents: America, Asia, Africa, and Europe. Impacts were compared by using the Generalized Least Squares analysis. The results showed that the audit committee reduced the profitability of two bank types. Moreover, it harmed the conventional banks’ efficiency but reported an unclear effect within Islamic banks. Even so, we noticed that the audit committee had a positive impact on the conventional banks’ liquidity, while the same effect was apparently ambiguous for the Islamic banks’ liquidity. For solvency, the audit committee positively influenced conventional banks while it affected that of Islamic banks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.236
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2021
Admission routes1
Has abstractyes

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